Font Size: a A A

Research On Multi-objective Optimal Scheduling Of Microgrid Based On Improved Particle Swarm Optimization Algorithm

Posted on:2021-05-03Degree:MasterType:Thesis
Country:ChinaCandidate:Z Q HuFull Text:PDF
GTID:2392330602978901Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Energy crisis and environmental crisis are the global common problems[1],and micro-grid may become the key to solve the crisis.Microgrid generally USES new energy as the power source,such as wind power and photovoltaic have been widely used in microgrid.Compared with the traditional power grid,the micro power grid has obvious advantages,such as flexibility,efficiency and environmental protection.With the large-scale development of microgrids,the collaborative cooperation of multiple microgrids in a certain region will become a trend,which can greatly reduce the operation cost,improve the power supply reliability and relieve the grid-connection pressure[2].However,the randomness of microgrid is due to the fact that the uncontrollable power supply is easily affected by the climatic environment.Therefore,if the operation cost or environmental problems are considered,the economy is obviously insufficient.In order to solve this problem,this paper mainly studies the multi-objective optimal scheduling problem of microgrid.The main work is as follows:(1)Six types of power generation units commonly used in micro power grid are introduced,including wind power generation,photovoltaic power generation,micro gas turbine,diesel generator,fuel cell and energy storage battery,and the output model analysis of these six types of micro power sources is carried out respectively.Then three objective functions are determined:1)economy;2)environmental protection;3)reliability.At the same time,the output of the power generation unit,the power balance,and the power exchange with the main network are constrained,and a relatively complete optimal dispatching model of the micro grid is formed.Finally,the optimal control strategy is given when the microgrid system is connected and isolated.(2)The operation strategy of energy storage devices in the micro-grid system is studied.Firstly,the most traditional peak cutting,valley filling and frequency modulation operation strategies are proposed.Then,the more commonly used fuzzy control strategy is analyzed.Compared with the peak-load strategy,the performance of the fuzzy control strategy is slightly improved,but the real-time performance of the fuzzy control method is not strong,and it is not suitable for the multi-objective optimization of micro-grid dispatching.Finally,on the basis of analyzing the deficiencies of the above two strategies,a dynamic programming operation strategy based on the remaining capacity of the energy storage device is proposed,which makes up for the deficiencies of the above two methods and is more comprehensive and real-time than other methods.(3)By designing strategies of global particle optimization and external file maintenance,the ability of traditional multi-objective particle swarm optimization algorithm to allocate load is improved[3].Furthermore,the preference of the decision-maker to the target is optimized through the scheme of fuzzy decision[4].Based on this method,an improved algorithm for multi-objective optimal scheduling of microgrid is proposed.This model algorithm can be used to better predict the level of micro-grid load,wind and light generation.Moreover,the improved multi-objective particle swarm optimization algorithm can select the optimal scheduling scheme from the non-inferior solutions.After applying the algorithm to a typical example,the ideal simulation results are obtained in both the micro-grid and off-grid operation,which proves the accuracy and feasibility of the proposed algorithm.At the same time,under the operation mode of parallel off-grid,by comparing the operation conditions under three battery control strategies(peak and valley cutting,frequency modulation,fuzzy control,and optimal planning control strategy based on battery capacity),it is concluded that the battery management method of dynamic planning proposed in this paper can make the system run more economically.(4)Fuzzy processing is carried out on the three objective functions to achieve the optimal performance of each objective function.Compared with the single-objective model,it is more in line with the actual operation situation,and the conclusion is drawn that the multi-objective model has higher reliability,stronger environmental protection and more practical application value than the single-objective model.
Keywords/Search Tags:Microgrid system, Improved particle swarm optimization, Optimal scheduling, Energy storage device, Fuzzy method
PDF Full Text Request
Related items